Machine Learning, Predictive Toxicology, Computational Genetics

Bahler, D., C. Wellington, B. Stone, and D. Bristol, Symbolic, Neural, and Bayesian Machine Learning Models for Predicting Carcinogenicity of Chemical Compounds, J. Chemical Information and Computer Sciences, 40(4), July/August 2000, 906-914. (Abstract) (242kb PDF)

Dennis Bahler and Laura Navarro, Methods for Combining Heterogeneous Sets of Classifiers, 17th Natl. Conf. on Artificial Intelligence (AAAI 2000), Workshop on New Research Problems for Machine Learning, 2000. (Abstract) (255kb PDF)

Dennis Bahler and Laura Navarro, Combining Heterogeneous Sets of Classifiers: Theoretical and Experimental Comparison of Methods, under review; full text temporarily offline. (Abstract) (637kb PDF)

Dennis Bahler and B. Stone, Neural Models and Extracted Rules for Knowledge Discovery in Predictive Toxicology, under review; full text temporarily offline. (Abstract) (393kb PDF)

C. Wellington and Dennis Bahler, Learning to Predict Carcinogenesis of Unstudied Chemicals in Rodents from Completed Rodent Trials, Mathematical Modeling and Scientific Computing, 8, 1997. (Abstract) (256kb PDF) A shorter version appears in Proc. 11th Intl. Conf. on Mathematical and Computer Modeling and Scientific Computing, Washington DC, April 1997.

Dennis Bahler and D. Bristol, The Induction of Rules for Predicting Chemical Carcinogenesis in Rodents, in L. Hunter, J. Shavlik, and D. Searls, eds. Intelligent Systems for Molecular Biology, Menlo Park, CA: AAAI/MIT Press, 1993, 29-37. (Abstract) (378kb PDF)

J. King and Dennis Bahler, "A Framework for the Study of Homophonic Ciphers in Classical Encryption and Genetic Systems," Cryptologia, Vol. XVII, No. 1, January 1993, 45-54.